Psychiatric disorders, particularly schizophrenia (SCZ), bipolar disorder (BD), and schizoaffective disorder (SAD), present significant diagnostic challenges. Current diagnostic methods rely on clinical observation and self-reported symptoms, leading to under-diagnosis and delayed treatment. To address this gap, we applied mass spectrometry-based metabolomic profiling and targeted analysis of inflammatory proteins to plasma samples from patients versus controls, aiming to uncover disease-related molecular patterns and enhance our understanding of the underlying pathophysiology of these complex disorders. This study included 26 patients with BD, 34 with SCZ, 16 with SAD, and age- and sex-matched controls. All diagnoses were established according to DSM-5 criteria. Unsupervised analysis shows a clear separation between controls and patients, indicating distinct metabolic and inflammatory profiles. However, the lack of clear differentiation among the three disease subgroups suggests shared biological profiles across these psychiatric disorders. Biomolecules driving this separation between controls and patients includes decreased levels of proinflammatory cytokines, amino acids, and glycerophospholipids, and increased levels of acylcarnitines. This study represents a step towards addressing the limitations of current diagnostic approaches to severe psychiatric disorders, which rely heavily on clinical symptoms, by using omics approaches to refine their diagnosis and treatment.